nanobot vs Paperclip
Which should you use? A side-by-side look at what each one does, who it suits, what it costs, how hard it is to set up, and where each falls short.
Open source · MIT
Self-hosted personal AI agent in Python that works through a browser, terminal, or chat apps.
Open source · MIT
Open-source Node.js and React app for organizing teams of AI agents around goals, tasks, and budgets.
The short answer
Choose nanobot if you need…
- People who want a self-hosted personal assistant they can inspect and customize
- Developers who want a small Python agent framework with memory, tools, and MCP support
- Users who want an assistant reachable from chat apps like Telegram, Discord, or Slack
- People who want to summarize PDF, Word, Excel, or PowerPoint files with an AI assistant
Choose Paperclip if you need…
- Developers already running several AI coding agents who want one place to track them
- Small teams experimenting with autonomous agents that need budgets and approval steps
- People who want an audit trail of what each agent did and why
- Anyone comfortable self-hosting a Node.js app
Side-by-side
| nanobot | Paperclip | |
|---|---|---|
| Type | App | App |
| Price | Free and open source | Free and open source |
| Licence | MIT | MIT |
| GitHub stars | 49.8k | 110k |
| Setup difficulty | Intermediate | Advanced |
| How you get it | Install with a package manager | Clone and build from source |
| Main language | Python | TypeScript |
| Last code update | 4 days ago | 4 days ago |
What each one is
nanobot
nanobot is an open-source personal AI assistant you run yourself. You can use it in a browser, a terminal, or chat apps like Telegram or Discord to work with files, remember preferences, and schedule tasks. It does not include a model; you connect it to a supported model provider or a local model server.
Paperclip
Paperclip is a Node.js server with a React dashboard that coordinates a team of AI agents to work toward business goals. You bring your own agents, assign goals, and track work and costs in one place. The README says it looks like a task manager but adds org charts, budgets, governance, and agent coordination underneath.
Best for
nanobot
- People who want a self-hosted personal assistant they can inspect and customize
- Developers who want a small Python agent framework with memory, tools, and MCP support
- Users who want an assistant reachable from chat apps like Telegram, Discord, or Slack
- People who want to summarize PDF, Word, Excel, or PowerPoint files with an AI assistant
Paperclip
- Developers already running several AI coding agents who want one place to track them
- Small teams experimenting with autonomous agents that need budgets and approval steps
- People who want an audit trail of what each agent did and why
- Anyone comfortable self-hosting a Node.js app
Strengths
nanobot
- Self-hosted, and the README says you can inspect and extend the code
- Works across a browser UI, terminal, and many chat channels
- Supports OpenAI-compatible APIs and local models, so you can choose your provider
Paperclip
- Works with many agent runtimes named in the README, including Claude Code, Codex, Cursor, and Gemini CLI
- Tracks tasks, costs, permissions, and run history in one dashboard
- MIT licensed and actively maintained, with a recent push in the repository metadata
Not ideal for
nanobot
- People who want a ready-made hosted service with no setup, since you must supply a model account or local model server
- Non-technical users who are uncomfortable with terminals or configuration, unless they follow the separate non-technical guide
- Teams needing a documented enterprise security model, since the README does not describe one in detail
Paperclip
- People who want a finished hosted product with no setup; the README points to a Paperclip Cloud waitlist rather than a live service
- Users who need a simple single-agent chat tool, since this is built for coordinating multiple agents
- Teams without a plan for reviewing agent output, because the README stresses verification and oversight
Trade-offs
nanobot
- Requires a model provider account or local model hardware, and costs depend on that choice
- The README is truncated and describes current source, which may differ from the stable release
- Setup involves Python and terminal steps for most users
Paperclip
- The README is truncated and mostly marketing-oriented, so setup details are unclear from this text alone
- Many described features, like Cloud, SSO, and phone management, may depend on hosted or paid offerings not verified here
- Coordinating autonomous agents adds risk and requires careful permission and budget setup
Getting started
nanobot
Install stable release with uv
uv tool install nanobot-aiInstall stable release with pip (inside an activated virtual environment)
python -m pip install nanobot-aiPaperclip
Clone the repository
git clone https://github.com/paperclipai/paperclip.gitFrequently asked questions
What is the difference between nanobot and Paperclip?
nanobot: Self-hosted personal AI agent in Python that works through a browser, terminal, or chat apps. Paperclip: Open-source Node.js and React app for organizing teams of AI agents around goals, tasks, and budgets. nanobot suits people who want a self-hosted personal assistant they can inspect and customize, while Paperclip suits developers already running several ai coding agents who want one place to track them.
Are nanobot and Paperclip free?
nanobot: Free and open source. Paperclip: Free and open source.
Which is easier to set up, nanobot or Paperclip?
nanobot is easier to get started with (rated intermediate); Paperclip is rated advanced and usually needs more setup.
Is nanobot or Paperclip more popular?
Paperclip has more GitHub stars (110k) than nanobot (49.8k). Popularity isn't the same as fit — check which one matches your use case above.
What are other alternatives to nanobot and Paperclip?
Other options people compare them with include LangChain, CowAgent, Reasonix, Horizon, Hermes Desktop.
Keep comparing
Built from our catalogue entries for both products: open-source details come from each project's README (AI-assisted, refreshed weekly) and GitHub data; AI-tool details are editorial. Spotted something wrong? Let us know from either product's page.